Data Scientist, Patterns

Tellwise Inc.; San Francisco, Northern (CA, KY); Hybrid; USD 120,000 - 150,000; Full time

Job summary

Tellwise Inc. is seeking a data scientist to build models that distinguish recurring versus one-off transactions and detect creep and anomalies.

In this role you will set thresholds, review results weekly, and maintain precision to minimize false alarms, ensuring trustworthy warnings for the product. This position emphasizes rigorous analysis and clear storytelling for non-analysts.

Qualifications

• Four or more years in applied data science, ideally on transactions or time series.
• You can write for a reader who is not an analyst and has four minutes.
• You are comfortable being the person who says the product is wrong about this.

Responsibilities

• Build models that classify recurring versus one-off, and detect creep and anomalies.
• Set thresholds: how sure is sure enough to show someone a warning.
• Review output weekly against labelled histories and file what is wrong, specifically.
• Keep false alarms rare. A warning nobody needed erodes trust in the one that mattered.

Skills

Applied data science

Time series analysis

Transactional data experience

Education

Four+ years in applied data science

Job description

When Tellwise says a subscription is creeping up, or that a charge was off-pattern, that claim has to come from somewhere defensible. You own where.

This is a research role with a product output. You decide how confidently Tellwise can call something recurring, and where it should stay quiet rather than guess.

What you would own

• Build the models that classify recurring versus one-off, and detect creep and anomalies.
• Set the thresholds: how sure is sure enough to show someone a warning.
• Review output weekly against labelled histories and file what is wrong, specifically.
• Keep false alarms rare. A warning nobody needed erodes trust in the one that mattered.

What we are looking for

• Four or more years in applied data science, ideally on transactions or time series.
• You can write for a reader who is not an analyst and has four minutes.
• You are comfortable being the person who says the product is wrong about this.
• You care about precision on warnings more than recall.

How hiring runs

A thirty-minute call with a founder, then a paid work session on a real problem from our backlog (three to four hours), then two conversations with people you would work alongside. Four steps, usually inside two weeks. We tell you where you stand at every one, and we reply either way.